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. Depending on the candidate's profile and interests, the thesis may develop along one or several of the following directions, at the crossroads of statistical physics, biophysics, and machine learning
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of biophysics, non-equilibrium statistical physics, and cancer biology. Its objective is to understand how stochastic fluctuations and cell-cell interactions combine to drive the spontaneous emergence
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of technological disruption driven by Artificial Intelligence, we propose to analyze the data and quantify these similarities by exploring various applications of machine learning methods. With the advancement of AI
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production. By developing hybrid architectures combining ontologies, generative models, reinforcement learning, and uncertainty quantification, the PhD project addresses the challenges identified by ICCARE in